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Swinburne’s strategy draws upon our understanding of future challenges. We choose to build Swinburne as the prototype of a new and different university – one that is truly of Technology, of Innovation and of
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or engineering Strong computer science skills and some experience with statistical, machine learning, and image processing techniques Strong candidates with electrical, mechanical, and biomedical engineering
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University of Technology Swinburne’s strategy draws upon our understanding of future challenges. We choose to build Swinburne as the prototype of a new and different university – one that is truly
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. • Proficient computer skills, including competence in the use of MS Office and other software packages, especially word processing, database and spreadsheet skills. About Swinburne University of Technology
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) and computer simulation (FEA) Experience in material characterisation and experimental testings Knowledge in impact dynamics Passionate and have interest in pursuing PhD degree. Experience in research
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the following skills and qualifications (tailored to the specific project): Driven individuals who want to be a part of a world class team Some familiarity in healthcare or engineering/image based analysis
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very high resolution, suitable for detecting photovoltaic modules and the cleanliness of solar panels. These images and other data can be processed by computer vision and machine learning methods
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publications and research experiences in structural dynamics and structural health monitoring, especially on computer vision, image processing, machine learning, deep learning, signal processing and data
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deep learning, imaging and data analysis would be helpful for this project. Must be eligible to enrol in PhD programs at Curtin University. Application process Please send your CV, academic transcripts
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to peer-reviewed academic publications Qualifications Completed undergraduate degree in physics, computer science, machine learning, computational modelling, or similar. About Swinburne University